On Precision Medicine. Q&A with Todd Winey

There a lots of ways to define Precision Medicine, but I like to look at it from a simple perspective. Being precise requires that we are more accurate in our practice of medicine. To be more precise in a knowledge driven field means having more data. The NIH defined their Precision Medicine Initiative as “a revolutionary approach for disease prevention and treatment that takes into account individual differences in lifestyle, environment, and biology.”

To me that means bringing together as much information about the patient to make more informed and more precisde decisions about their healthcare.

Q2. Does Precision Medicine work in practice?

I believe it does, once you move off of the idea that Precision Medicine is solely about the genomic aspects of health. Every day we make strides in healthcare, using data more effectively, making discoveries and seeing what works to help patients. So in some ways we’re being more precise every day. It is an incremental improvement, the kinds that often don’t make headlines, but continue to make progress.

Q3. What are the key obstacles in delivering Precision Medicine?

Since I tend to view Precision Medicine thru a data science lens, the key obstacle is always about the data. How do we share more, how do we achieve “data liquidity” inside healthcare organizations? And once we’ve shared it, how do we combine previously unrelated data sets to realize new insights.

We’re learning, and we’re learning how to work on these new healthcare data problems at scale. You have to remember, the human genome project was completed in 2003. In the US, its only been as of about 2015 that we’ve had 90%+ penetration of Electronic Medical Records (EMRs). So a lot of this digital healthcare information is brand new.

Q4. What is your take on the initiative of the National Institutes of Health, first announced as Precision Medicine Initiative — and subsequently redubbed “All of Us” ? (*)

Well, I certainly agree with their definition of Precision Medicine. I also applaud the effort for the basic science that it is. In the early stages of where we are with Precision Medicine, government funded research can be beneficial to jumpstarting some of the infrastructure. Adding a data set of 1M individuals can be a real boost to research. It wasn’t so long ago that we were looking at projects of 1000 genomes, and now its ramping up to 100,000 Genomes and 1M. I think it is also important that the All of Us project is keeping an eye on the diversity of the sample set. A lot of the early data sets were focused on more homogenous populations or particular diseases.

Q5. What technologies are available for implementing an effective Precision Medicine?

Because I’m an incrementalist, there are a whole range of technologies that are driving Precision Medicine. Of course sequencing is getting faster and cheaper, we’re in sight of the $1000 genome, and secondary analysis is getting amazing fast to the point where it can be clinically useful. Specialized compute resources and GPUs are turning what used to be days of number crunching into hours and minutes. That’s pretty cool. On the data side, we’re seeing a lot of progress with AI/DL/ML techniques to mine these new data sets. I don’t think AI will magically create eureka cures, but what it is really improving is the pace of change, the pace of research. The ability to comb through data sets in hours instead of months is pushing the discovery cycle. And of course there is a lot of “big data” technology that makes solving these problems at scale cost effective. That’s what we do at InterSystems.

Q6. What is the road ahead for Precision Medicine?

I think we’re seeing a wonderful convergence. Healthcare is creating a tremendous amount of data. Healthcare is finally fully digital for the most part. And we have a lot of really cool technology at our disposal to figure out how best to use in pursuit of Precision Medicine. I think the road ahead will continue with accelerated discovery, healthcare organizations really learning how to make use of the newly understood data, and hopefully in the next decade, we won’t be taking about Precision Medicine anymore, just Medicine.